def load_and_extract_center(datum, data_prefix):
"""
Load image and computer optimal center
"""
full_image_path = os.path.join(data_prefix, datum["short_file_path"])
image = reading_images.read_image_png(full_image_path)
return datum["short_file_path"], extract_center(datum, image)
def get_optimal_center_single(cropped_mammogram_path, metadata_path):
"""
Get optimal center for single example
"""
metadata = pickling.unpickle_from_file(metadata_path)
image = reading_images.read_image_png(cropped_mammogram_path)
optimal_center = get_optimal_centers.extract_center(metadata, image)
metadata["best_center"] = optimal_center
pickling.pickle_to_file(metadata_path, metadata)
def load_image(image_path, view, horizontal_flip):
"""
Loads a png or hdf5 image as floats and flips according to its view.
"""
if image_path.endswith("png"):
image = read_image_png(image_path)
elif image_path.endswith("hdf5"):
image = read_image_mat(image_path)
else:
raise RuntimeError()
image = image.astype(np.float32)
image = flip_image(image, view, horizontal_flip)
return image
def crop_mammogram_one_image(scan, input_file_path,
output_file_path, num_iterations,
buffer_size):
"""
Crops a mammogram, saves as png file, includes the following additional information:
- window_location: location of cropping window w.r.t. original dicom image so that segmentation
map can be cropped in the same way for training.
- rightmost_points: rightmost nonzero pixels after correctly being flipped
- bottommost_points: bottommost nonzero pixels after correctly being flipped
- distance_from_starting_side: number of zero columns between the start of the image and start of
the largest connected component w.r.t. original dicom image.
"""
image = reading_images.read_image_png(input_file_path)
try:
# error detection using erosion. Also get cropping information for this image.
cropping_info = crop_img_from_largest_connected(
image,
image_orientation(scan['horizontal_flip'],
scan['side']), True, num_iterations,
buffer_size, 1 / 3)
except Exception as error:
print(
input_file_path,
"\n\tFailed to crop image because image is invalid.",
str(error))
else:
top, bottom, left, right = cropping_info[0]
target_parent_dir = os.path.split(output_file_path)[0]
if not os.path.exists(target_parent_dir):
os.makedirs(target_parent_dir)
try:
saving_images.save_image_as_png(
image[top:bottom, left:right], output_file_path)
except Exception as error:
print(input_file_path, "\n\tError while saving image.",
str(error))
return cropping_info
